CN112732149B - Novel method for displaying software interactive interface based on AI technology - Google Patents
Novel method for displaying software interactive interface based on AI technology Download PDFInfo
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- CN112732149B CN112732149B CN202011642071.3A CN202011642071A CN112732149B CN 112732149 B CN112732149 B CN 112732149B CN 202011642071 A CN202011642071 A CN 202011642071A CN 112732149 B CN112732149 B CN 112732149B
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- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
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Abstract
The invention belongs to the technical field of interactive interface generation, and particularly discloses a novel method for displaying a software interactive interface based on an AI technology, wherein when a user uses a software system, the user is judged whether to use the software for the first time, if so, whether the corresponding role of the user in an enterprise has been operated is judged, and if not, an AI interactive engine calls data in a habit history library of the user for analysis to generate a dynamic interface; when the corresponding role of the user in the enterprise is not operated, judging whether the corresponding role of the user has historical data in the enterprise, if so, calling the data in an industry habit historical library by an AI interactive engine for analysis to generate a dynamic interface; when the role corresponding to the user has no historical data in the enterprise industry, judging whether the role corresponding to the user has historical data, if not, calling a general flow standard library by an AI interactive engine and generating a standard interface; if so, the AI interactive engine calls the data in the character habit history library for analysis to generate a dynamic interface.
Description
Technical Field
The invention relates to the technical field of interactive interface generation, in particular to a novel method for displaying a software interactive interface based on an AI technology.
Background
At present, all enterprise-oriented software systems have fixed menu selection, page display layout and page display elements, and different users can see the same human-computer interaction interface including the menu selection, the page display layout and the page display elements when logging in the system.
The current software system can not dynamically display a man-machine interaction interface which is specially customized for a user according to the use habit of the user, the characteristics of an enterprise client where the user is located, the industrial characteristics of the industry where the user is located, or the general flow of the role to which the user belongs, wherein the man-machine interaction interface comprises menu selection, surface display layout and page display elements. The fixed man-machine interaction interface on one side of thousands of people can restrict the efficiency of different users in using the software system.
Disclosure of Invention
The invention aims to provide a novel method for displaying a software interactive interface based on an AI technology, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a novel method for displaying a software interactive interface based on AI technology comprises the following steps:
when a user uses the software system, judging whether the user uses the software system for the first time, if so, judging whether the corresponding role of the user in an enterprise where the user is located in the enterprise has been operated, if not, calling data in a user habit history library by an AI interactive engine for analysis, and generating a dynamic interface based on the user habits;
if the corresponding role of the user in the enterprise is not operated, judging whether the corresponding role of the user has historical data in the enterprise, if so, calling the data in an enterprise habit history library by an AI interactive engine for analysis to generate a dynamic interface based on the use habits of the corresponding role of the user in the enterprise; in the industry of the enterprise, when the corresponding role of the user has historical data, an AI interactive engine calls data in an industry habit history library for analysis to generate a dynamic interface based on the use habits of the corresponding role of the user in the industry;
if the role corresponding to the user has no historical data in the enterprise industry, judging whether the role corresponding to the user has cross-industry historical data, if not, calling a general process standard library by an AI interactive engine and generating a standard interface based on preset data in the general process standard library; if so, the AI interactive engine calls the data in the character habit history base for analysis to generate a dynamic interface based on the use habits of the corresponding characters of the user.
Preferably, the general process standard library refers to a standard database table stored according to different roles of industry and enterprise management and according to different categories of business modules.
Preferably, the user habit history base refers to a database table storing all usage records of all users.
Preferably, the character habit history library refers to a database table of cross-industry user usage records queried according to characters.
Preferably, the enterprise habit history base refers to a database table of user usage records queried according to enterprises and roles.
Preferably, the industry habit history database refers to a database table of user usage records queried according to industry and roles.
Preferably, the AI interaction engine includes machine learning techniques and big data normative analysis techniques.
Preferably, the dynamic interface is generated by an AI interaction engine and transmits instructions and operations issued by a user to the AI interaction engine.
Preferably, the operation steps of the dynamic interface are as follows: firstly, a user operates or sends an instruction on a dynamic interface; then, the dynamic interface sends the user operation and instruction to the AI interactive engine in real time, and simultaneously, the dynamic interface sends all the actions of the user to the AI interactive engine; then, the AI interactive engine executes reading or updating operation on the corresponding service module according to the instruction and operation of the user, and simultaneously stores the instruction, operation and action of all the users in a user habit history base; and then, the AI interactive engine extracts and updates data from the habit history library, analyzes the data and updates the data to the enterprise habit history library, the industry habit history library and the role habit history library.
Compared with the prior art, the invention has the beneficial effects that:
1. the AI interactive engine is arranged, so that a machine learning technology and a big data normative analysis technology can be combined, learning and analysis can be performed according to data of user habits, and business data precipitated in an enterprise business module and business data precipitated in the industry where an enterprise is located can be normalized and analyzed; meanwhile, the system has deep knowledge not only on the user, but also on the business of the enterprise and the industry where the user is located, and the human-computer interaction interface dynamically generated based on the knowledge is more in line with the requirements of the user and the business double-layer.
2. All elements on the human-computer interaction interface are dynamically generated through machine learning, a user does not need to learn and search menu items corresponding to actions expected to be completed in the using process, the system can guide the user to complete needed operations quickly and efficiently, and therefore the system using efficiency of the user can be improved.
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FIG. 1 is a flow chart of the method of embodiment 1 of the present invention;
fig. 2 is a schematic diagram of the operation steps of the dynamic interface according to embodiment 2 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1: referring to fig. 1, the present invention provides a technical solution: a novel method for displaying a software interactive interface based on AI technology comprises the following steps:
the method comprises the following steps: when a user uses the software system, judging whether the user uses the software system for the first time, if so, judging whether the corresponding role of the user in an enterprise where the user is located in the enterprise has been operated, if not, calling data in a user habit history library by an AI interactive engine for analysis, and generating a dynamic interface based on the user habits;
step two: if the role corresponding to the user in the enterprise is not operated, judging whether the role corresponding to the user in the enterprise has historical data, if so, calling the data in an enterprise habit history library by an AI interactive engine for analysis to generate a dynamic interface based on the use habit of the role corresponding to the user in the enterprise; in the industry of the enterprise, when the corresponding role of the user has historical data, an AI interactive engine calls the data in an industry habit history library for analysis to generate a dynamic interface based on the use habit of the corresponding role of the user in the industry;
step three: in the industry of the enterprise, when the role corresponding to the user has no historical data, judging whether the role corresponding to the user has cross-industry historical data, if not, calling a general flow standard library by an AI interactive engine and generating a standard interface based on preset data in the general flow standard library; if so, the AI interactive engine calls the data in the character habit history base for analysis to generate a dynamic interface based on the use habits of the corresponding characters of the user.
By arranging the AI interactive engine, the machine learning technology and the big data normative analysis technology can be combined, so that the learning analysis can be carried out according to the data of user habits, and the business data precipitated in an enterprise business module and the business data precipitated in the industry where the enterprise is located can be normalized and analyzed; meanwhile, the system has deep knowledge not only on the user, but also on the business of the enterprise and the industry where the user is, and the dynamic interface dynamically generated based on the knowledge is more in line with the needs of the user and the business.
The user habit history library in the step one refers to a database table for storing all usage records of all users. These records include all historical data per user, per menu item click data stored by the business module, form fill data, business page forward cancel or return data, business module usage data, text filled in using feedback input boxes, and the like.
And the enterprise habit historical library in the step two refers to a database table of user use records inquired according to enterprises and roles. These records include all historical data, by business, by role, by menu item click data queried by business module, form fill data, business page forward cancel or return data, business module usage data, text filled in using feedback input boxes, and so forth. The enterprise habit historical library is extracted from the user habit historical library.
And the industry habit historical library in the step two refers to a database table of user use records inquired according to industry and roles. The records comprise menu item click data and forms which are inquired according to industry, role and business module. These records include all historical data, by industry, by role, by menu item click data queried by business module, form fill data, business page forward cancel or return data, business module usage data, text filled in using feedback input boxes, and so on. The industry habit historical library is extracted from the user habit historical library.
The general process standard library in the third step is a standard database table stored according to different categories of industry, enterprise management and business modules. For example, a production supervisor at a manufacturing facility may set standard menu items, standard forms, standard pre-fill data in the forms, standard business page display sequences, and standard business page display content in the production data purchasing software. The standard data can be stored in the general process library in advance according to industry (manufacturing industry), enterprise management role (production supervisor) and business module (production data purchase). Another example is all standard data (menus, forms, pre-fill data, page display order, page display content) for human resource software (business modules) by the human executive (role) of the internet software (industry). This is also part of the generic flow library.
And step three, the character habit historical library refers to a database table of cross-industry user usage records inquired according to the characters. These records include all historical data by role, menu item click data by business module query, form fill data, business page forward cancel or return data, business module usage data, text filled in using feedback input boxes, and so on. The character habit historical library is extracted from the user habit historical library.
The AI interactive engine in the first step, the second step and the third step uses a machine learning technology and a big data normative analysis technology, self-learning is carried out on a large amount of data extracted from different historical libraries, and an algorithm for iterative big data normative analysis is continuously adjusted by using the data, so that the capability of deducing dynamic and personalized software interfaces which are most in line with the habits of users and most meet the business needs of enterprises is continuously improved;
when the machine learning technology is introduced, the AI interactive engine can continuously extract a large amount of user, enterprise and industry data from different historical libraries and use the data to carry out self-learning, so that the user habits of different users, the business characteristics of different enterprises and the industry best practices of different industries can be known by the self.
When a big data normative analysis technology is introduced, an AI interactive engine continuously extracts a large amount of user, enterprise and industry data from different historical libraries, and the data is used for continuously adjusting the algorithm of iterative big data normative analysis, so that the balance of influence degree of the data of three dimensions of the user, the enterprise and the industry on the total algorithm of the engine can be continuously kept.
In this embodiment, the dynamic interface is generated by the AI interaction engine and passes the commands and operations issued by the user to the AI interaction engine.
Example 2: referring to fig. 2, in this embodiment, based on embodiment 1, further, the operation steps of the state interface are as follows:
step S1: a user operates or sends an instruction on the dynamic interface;
step S2: the dynamic interface sends user operation and instructions to the AI interactive engine in real time, and simultaneously, the dynamic interface sends all actions of the user to the AI interactive engine;
and step S3: the AI interactive engine executes reading or updating operation on the corresponding service module according to the instruction and operation of the user, and simultaneously stores the instruction, operation and action of all the users in a user habit history library;
and step S4: and the AI interactive engine extracts and updates data from the habit history library, and updates the data to the enterprise habit history library, the industry habit history library and the role habit history library after analysis.
In the embodiment, all elements on the dynamic interface are dynamically generated through machine learning, so that a user does not need to learn and search menu items corresponding to actions to be completed in the using process, the system can guide the user to complete required operations quickly and efficiently, and the system using efficiency of the user can be improved.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A novel method for displaying a software interactive interface based on AI technology is characterized by comprising the following steps:
when a user uses the software system, judging whether the user uses the software system for the first time, if so, judging whether the corresponding role of the user in an enterprise where the user is located has been operated, if not, calling data in a user habit history library by an AI interactive engine for analysis, and generating a dynamic interface based on the user habits;
if the corresponding role of the user in the enterprise is not operated, judging whether the corresponding role of the user has historical data in the enterprise, if so, calling the data in an enterprise habit history library by an AI interactive engine for analysis to generate a dynamic interface based on the use habits of the corresponding role of the user in the enterprise; in the industry of the enterprise, when the corresponding role of the user has historical data, an AI interactive engine calls data in an industry habit history library for analysis to generate a dynamic interface based on the use habits of the corresponding role of the user in the industry;
in the industry of the enterprise, when the role corresponding to the user has no historical data, judging whether the role corresponding to the user has cross-industry historical data, if not, calling a general flow standard library by an AI interactive engine and generating a standard interface based on preset data in the general flow standard library; if so, the AI interactive engine calls the data in the character habit history base for analysis to generate a dynamic interface based on the use habits of the corresponding characters of the user.
2. The AI technology based novel method of displaying a software interactive interface as claimed in claim 1, wherein: the general process standard library refers to a standard database table stored according to different roles of industry, enterprise management and business module classification.
3. The novel method for displaying a software interactive interface based on AI technology of claim 1, wherein: the user habit history database refers to a database table that stores all usage records of all users.
4. The AI technology based novel method of displaying a software interactive interface as claimed in claim 1, wherein: the character habit history base refers to a database table of cross-industry user usage records queried according to characters.
5. The novel method for displaying a software interactive interface based on AI technology of claim 1, wherein: the enterprise habit history library refers to a database table of user usage records inquired according to enterprises and roles.
6. The novel method for displaying a software interactive interface based on AI technology of claim 1, wherein: the industry habit historical library refers to a database table of user usage records inquired according to industry and roles.
7. The AI technology based novel method of displaying a software interactive interface as claimed in claim 1, wherein: the AI interactive engine comprises a machine learning technology and a big data normative analysis technology.
8. The AI technology based novel method of displaying a software interactive interface as claimed in claim 1, wherein: the dynamic interface is generated by the AI interactive engine and transmits the instructions and operations sent by the user to the AI interactive engine.
9. The novel method for displaying a software interactive interface based on AI technology of claim 1, wherein: the operation steps of the dynamic interface are as follows: firstly, a user operates or gives an instruction on a dynamic interface; then, the dynamic interface sends the user operation and instruction to the AI interactive engine in real time, and simultaneously, the dynamic interface sends all the actions of the user to the AI interactive engine; then, the AI interactive engine executes reading or updating operation on the corresponding service module according to the instruction and operation of the user, and simultaneously stores the instruction, operation and action of all the users in a user habit history base; and then, the AI interactive engine extracts and updates data from the user habit history library, analyzes the data and updates the data to the enterprise habit history library, the industry habit history library and the role habit history library.
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